imshow¶

In [1]:

import numpy as np
from skimage.io import imread
from skimage.measure import label
import stackview
import matplotlib.pyplot as plt

Visualizing images¶

The imshow function serves showing images, similar to matplotlib.pyplot.imshow, just with a little more convenience.

In [2]:

image = imread("data/blobs.tif")

stackview.imshow(image)

You can also activate axes descriptions and a colorbar to better read the values.

In [3]:

stackview.imshow(image, axes=True, colorbar=True)

If you work with colormaps, also pure_... colormaps introduced in microfilm work.

In [4]:

stackview.imshow(image, axes=True, colorbar=True, colormap='pure_magenta')

Label images¶

Label images are automatically shown with a coloured visualization:

In [5]:

binary = image > 128
labels = label(binary)

stackview.imshow(labels)

Combining images¶

You can also overlay images by setting continue_drawing=True and showing another image using a given alpha value:

In [6]:

stackview.imshow(image, continue_drawing=True)
stackview.imshow(labels, alpha=0.4)

Sub-plots¶

This might be especially useful when combinging sub-plots using matplotlib.

In [7]:

fig, axs = plt.subplots(1, 3, figsize=(15,15))

stackview.imshow(image, plot=axs[0], title='image', axes=True)
stackview.imshow(labels, plot=axs[1], title='labels')
stackview.imshow(image, plot=axs[2], continue_drawing=True)
stackview.imshow(labels, plot=axs[2], alpha=0.4, title='image + labels')

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